1. Field of the Invention
The present invention relates generally to computer software, and more particularly to relationship management software for classifying and responding to customer communications.
2. Description of the Prior Art
Most commercial enterprises devote significant time and resources to the tasks of reviewing and appropriately responding to inquiries, requests and other text-based electronic communications received from current or prospective customers. In order to enable more efficient administration of these tasks, certain software vendors, such as iPhrase Technologies, Inc. of Cambridge, Mass., have developed computerized customer relationship management (CRM) systems which perform analysis of incoming electronic communications and classify the communications into predetermined categories based on the determined intent. This categorization process may be utilized to automate generation of responses, or to guide human agents in the selection of a suitable response.
Such CRM systems typically require construction of a knowledge base (KB) before the analysis and classification functions may be performed reliably, i.e., before the CRM system may be put on-line. The KB contains relevant statistical and semantic information derived from a body of sample texts (known collectively as a corpus) by using a process known as training. KB performance may be improved by periodically retraining the KB with additional texts, or by providing the KB with online feedback (a process referred to as online learning, an example of which is described in U.S. patent application Ser. No. 09/754,179, filed Jan. 3, 2001). Generally, the accuracy and reliability of a CRM system depend on optimizing and maintaining KB performance. Poor KB performance may result in unacceptably high rates of false positives (i.e., frequently assigning non-relevant categories to communications) and/or false negatives (i.e., frequently failing to assign a relevant category to communications).
To construct and train a KB that provides satisfactory performance, the CRM user must carefully perform a number of preparatory tasks, including collecting appropriate sample texts, identifying a set of categories that classify the texts according to intent, and assigning the proper category to each sample text. If this process is conducted improperly or if erroneous information is used, then the performance of the resultant KB will be compromised, and the associated CRM system will behave in an unreliable fashion. Unfortunately, the prior art lacks tools for testing the performance of a KB and for reporting the test results in a manner which would allow the user to identify and remedy errors and problematic conditions in order to improve KB performance.